方案一可借鉴轮子：

https://github.com/wuyuewuzhenmin/Jmeter-ptc

方案二可借鉴轮子：

https://github.com/myzhan/boomer

你都从 yaml 文件里面拿到了所有的请求和参数这一些，接下来不就像写接口测试脚本一样吗，把对应的参数放到 python 的脚本里面对应的位置，然后用 requests 去执行。所谓的 testsuite testcase teststep ，无非就是执行过程中的先后顺序，然后再去遍历执行每个过程中又嵌套的 testsuite testcase teststep。

""" Running testcases. """
   Examples:
       >>> tests_mapping = {
               "project_mapping": {
                   "functions": {}
               },
               "testcases": [
                   {
                       "config": {
                           "name": "XXXX",
                           "base_url": "http://127.0.0.1",
                           "verify": False
                       },
                       "teststeps": [
                           {
                               "name": "test description",
                               "variables": [],        # optional
                               "request": {
                                   "url": "http://127.0.0.1:5000/api/users/1000",
                                   "method": "GET"
                               }
                           }
                       ]
                   }
               ]
           }

       >>> testcases = parser.parse_tests(tests_mapping)
       >>> parsed_testcase = testcases[0]

       >>> test_runner = runner.Runner(parsed_testcase["config"])
       >>> test_runner.run_test(parsed_testcase["teststeps"][0])

首先，校验 yaml 文件的格式，返回 yaml 的数据。

def load_yaml_file(yaml_file):
    """ load yaml file and check file content format
    """
    with io.open(yaml_file, 'r', encoding='utf-8') as stream:
        yaml_content = yaml.load(stream)
        _check_format(yaml_file, yaml_content)
        return yaml_content

接下来，根据你的测试指令后的文件的后缀名，读取对应格式的文件。

def load_file(file_path):
    if not os.path.isfile(file_path):
        raise exceptions.FileNotFound("{} does not exist.".format(file_path))

    file_suffix = os.path.splitext(file_path)[1].lower()
    if file_suffix == '.json':
        return load_json_file(file_path)
    elif file_suffix in ['.yaml', '.yml']:
        return load_yaml_file(file_path)
    elif file_suffix == ".csv":
        return load_csv_file(file_path)
    else:
        # '' or other suffix
        err_msg = u"Unsupported file format: {}".format(file_path)
        logger.log_warning(err_msg)
        return []

然后，下面这个我觉得就很明显了。

def load_teststep(raw_testinfo):
  ...

def load_testcase(raw_testcase):
  ...

def load_testcase_v2(raw_testcase):
  """ load testcase in format version 2. """
  ...

def load_testsuite(raw_testsuite):
  ...

剩下一些类似 __extend_with_api_ref() __extend_with_testcase_ref() 等等的函数，无非就是读取你的测试步骤中调用的扩展 api 或者 testcase，locate_debugtalk_py() 函数作用就更明显了。一系列相关的东西都加载完，最后开始 load_test 进行最后的汇总组合。

def load_tests(path, dot_env_path=None):
    """ load testcases from file path, extend and merge with api/testcase definitions.

    Args:
        path (str): testcase/testsuite file/foler path.
            path could be in 2 types:
                - absolute/relative file path
                - absolute/relative folder path
        dot_env_path (str): specified .env file path

    Returns:
        dict: tests mapping, include project_mapping and testcases.
              each testcase is corresponding to a file.
            {
                "project_mapping": {
                    "PWD": "XXXXX",
                    "functions": {},
                    "env": {}
                },
                "testcases": [
                    {   # testcase data structure
                        "config": {
                            "name": "desc1",
                            "path": "testcase1_path",
                            "variables": [],                    # optional
                        },
                        "teststeps": [
                            # test data structure
                            {
                                'name': 'test desc1',
                                'variables': [],    # optional
                                'extract': [],      # optional
                                'validate': [],
                                'request': {}
                            },
                            test_dict_2   # another test dict
                        ]
                    },
                    testcase_2_dict     # another testcase dict
                ],
                "testsuites": [
                    {   # testsuite data structure
                        "config": {},
                        "testcases": {
                            "testcase1": {},
                            "testcase2": {},
                        }
                    },
                    testsuite_2_dict
                ]
            }

    """
    if not os.path.exists(path):
        err_msg = "path not exist: {}".format(path)
        logger.log_error(err_msg)
        raise exceptions.FileNotFound(err_msg)

    if not os.path.isabs(path):
        path = os.path.join(os.getcwd(), path)

    load_project_tests(path, dot_env_path)
    tests_mapping = {
        "project_mapping": project_mapping
    }

    def __load_file_content(path):
        loaded_content = None
        try:
            loaded_content = load_test_file(path)
        except exceptions.FileFormatError:
            logger.log_warning("Invalid test file format: {}".format(path))

        if not loaded_content:
            pass
        elif loaded_content["type"] == "testsuite":
            tests_mapping.setdefault("testsuites", []).append(loaded_content)
        elif loaded_content["type"] == "testcase":
            tests_mapping.setdefault("testcases", []).append(loaded_content)
        elif loaded_content["type"] == "api":
            tests_mapping.setdefault("apis", []).append(loaded_content)

    if os.path.isdir(path):
        files_list = load_folder_files(path)
        for path in files_list:
            __load_file_content(path)

    elif os.path.isfile(path):
        __load_file_content(path)

    return tests_mapping

总之，多看看源码就好辣 hhh
源码：https://github.com/httprunner/httprunner
回答问题的相关代码文件： ./httprunner/loader.py

ppts v1.4.0: 当输出格式为 json 时，支持通过 webhook 发送测试数据给群机器人

ppts 安装需要 node 环境，版本最好是最新的，有使用问题或技术问题可以直接到 Github 上提 issues，或此处留言。如果对你的使用有帮助，请点赞或 Star 一下 ~